Delgadowalsh9748
Previous research has proven the strong influence of emotions on student engagement and motivation. Therefore, emotion recognition is becoming very relevant in educational scenarios, but there is no standard method for predicting students' affects. However, physiological signals have been widely used in educational contexts. Some physiological signals have shown a high accuracy in detecting emotions because they reflect spontaneous affect-related information, which is fresh and does not require additional control or interpretation. Most proposed works use measuring equipment for which applicability in real-world scenarios is limited because of its high cost and intrusiveness. To tackle this problem, in this work, we analyse the feasibility of developing low-cost and nonintrusive devices to obtain a high detection accuracy from easy-to-capture signals. By using both inter-subject and intra-subject models, we present an experimental study that aims to explore the potential application of Hidden Markov Models (HMM) to predict the concentration state from 4 commonly used physiological signals, namely heart rate, breath rate, skin conductance and skin temperature. We also study the effect of combining these four signals and analyse their potential use in an educational context in terms of intrusiveness, cost and accuracy. The results show that a high accuracy can be achieved with three of the signals when using HMM-based intra-subject models. However, inter-subject models, which are meant to obtain subject-independent approaches for affect detection, fail at the same task.Tiger nut (Cyperus esculentus), a perennial C4 plant of the Cyperaceae family, is an unconventional crop that is distinguished by its oil-rich tubers, which also possesses the advantages of strong resistance, wide adaptability, short life periods, and large biomass. To facilitate studies on gene expression in this species, we identified and validated a series of reference genes (RGs) based on transcriptome data, which can be employed as internal controls for qRT-PCR analysis in tiger nut. Fourteen putative candidate RGs were identified and evaluated across nine different tissues of two cultivars, and the RGs were analyzed using three different algorithms (geNorm, NormFinder, and BestKeeper). The stability rankings of the candidate RGs were merged into consensus lists with RankAggreg. For the below-ground storage organ of tiger nut, the optimal RGs were TUB4 and UCE2 in different developmental stages of tubers. UCE2 and UBL5 were the most stably expressed RGs among all tissues, while Rubisco and PGK exhibited the lowest expression stability. UCE2, UBL5 and Rubisco were compared to normalize the expression levels of the caleosin (CLO) and diacylglycerol acyltransferase 2-2 (DGAT2-2) genes across the same tissues. Our results showed that the RGs identified in this study, which exhibit more uniform expression patterns, may be utilized for the normalization of qRT-PCR results, promoting further research on gene expression in various tissues of tiger nut.Despite the importance of patient safety in home-care nursing provided by licensed nurses in patients' homes, little is known about the nationwide incidence of adverse events in Japan. This article describes the incidence of adverse events among home-care nursing agencies in Japan and investigates the characteristics of agencies that were associated with adverse events. A cross-sectional nationwide self-administrative questionnaire survey was conducted in March 2020. The questionnaire included the number of adverse event occurrences in three months, the process of care for patient safety, and other agency characteristics. Of 9979 agencies, 580 questionnaires were returned and 400 were included in the analysis. The number of adverse events in each agency ranged from 0 to 47, and 26.5% of the agencies did not report any adverse event cases. The median occurrence of adverse events was three. In total, 1937 adverse events occurred over three months, of which pressure ulcers were the most frequent (80.5%). Adjusting for the number of patients in a month, the percentage of patients with care-need level 3 or higher was statistically significant. Adverse events occurring in home-care nursing agencies were rare and varied widely across agencies. The patients' higher care-need levels affected the higher number of adverse events in home-care nursing agencies.The impermeable cover in urban area has been growing due to rapid urbanization, which prevents stormwater from being naturally infiltrated into the ground. There is a higher chance of flooding in urban area covered with conventional concretes and asphalts. The permeable pavement is one of Low-Impact Development (LID) technologies that can reduce surface runoff and water pollution by allowing stormwater into pavement systems. Unlike traditional pavements, permeable pavement bases employ open-graded aggregates (OGAs) with highly uniform particle sizes. There is very little information on the engineering properties of compacted OGAs. In this study, the moduli of open-graded aggregates under various compaction energies are investigated based on the Plate Load Test (PLT) and Light-Weight Deflectometer (LWD). Artificial Neural Network (ANN) and Linear Regression (LR) models are employed for estimation of the moduli of the aggregates based on the material type and level of compaction. Overall, the moduli from PLT and LWD steeply increase until the number of roller passes reaches 4, and they gradually increase until the number of roller passes becomes 8. A set of simple linear equations are proposed to evaluate the moduli of open-graded aggregates from PLT and LWD based on the material type and the number of roller passes.The synchronization of time between devices is one of the more important and challenging problems in wireless networks. We discuss the problem of maximization of the probability of receiving a message from a device using a limited listening time window to minimize energy utilization. https://www.selleckchem.com/products/abt-199.html We propose a solution to two important problems in wireless networks of battery-powered devices a method of establishing a connection with a device that has been disconnected from the system for a long time and developed unknown skew and also two approaches to follow-up clock synchronization using the confidence interval method. We start with the analysis of measurements of clock skew. The algorithms are evaluated using extensive simulations and we discuss the selection of parameters balancing between minimizing the energy utilization and maximizing the probability of reception of the message. We show that the selection of a time window of growing size requires less energy to receive a packet than using the same size of time window repeated multiple times.